Xu Juan, Chutatape Opas
Biomedical Engineering Research Centre, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
Comput Biol Med. 2006 Sep;36(9):921-40. doi: 10.1016/j.compbiomed.2005.05.001. Epub 2005 Jul 14.
Three-dimensional (3-D) visualization of the optic nerve head (optic disk) is very useful for clinical applications. It allows clinicians to measure the disk parameters more accurately and thus make the pathological diagnosis and progression monitoring easier. This paper describes an automatic, precise, 3-D optic nerve head reconstruction method from a pair of stereo images for which efficient steps including sparse-image registration and dense-depth recovery are used. A combination of two registration methods is used to detect the sub-pixel correspondences. The proposed method takes advantages of both the correlation methods which is robust to noise and the feature-based method on its accuracy. The searching range in image registration is auto-adjusted based on the previous iteration result. Only sparse matched points are computed to speed up the processing and the sub-pixel matching is used to overcome the problem of low resolution in the image. This is followed by the piecewise cubic interpolation to obtain the dense disparities and depths. Multiple windowing is applied here by first using the large window to obtain basic disparities followed by the small window and previous basic disparities to measure details. The result is then smoothed and displayed as the final 3-D shape.
视神经乳头(视盘)的三维(3-D)可视化在临床应用中非常有用。它使临床医生能够更准确地测量视盘参数,从而更轻松地进行病理诊断和病情进展监测。本文描述了一种从一对立体图像中自动、精确地重建三维视神经乳头的方法,该方法使用了包括稀疏图像配准和密集深度恢复在内的有效步骤。结合两种配准方法来检测亚像素对应关系。所提出的方法利用了对噪声具有鲁棒性的相关方法和基于特征方法的准确性。图像配准中的搜索范围根据上一次迭代结果自动调整。仅计算稀疏匹配点以加快处理速度,并使用亚像素匹配来克服图像分辨率低的问题。接下来是分段三次插值以获得密集的视差和深度。这里应用了多窗口技术,首先使用大窗口获得基本视差,然后使用小窗口和先前的基本视差来测量细节。然后对结果进行平滑处理并显示为最终的三维形状。